CC0002 Notes Summary (without additional readings) PDF

Module 1: Computational Thinking Computational Thinking Competencies Computational: Involving the calculation of answers, amounts, results (e.g., calculations, order) Thinking: The activity of u (e.g., reasoning, questioning) Competencies: Important skills that are needed to do a job (e.g., managerial competencies) Includes: 1. Abstraction - Identifying and utilizing the structure of concepts / main ideas - Simplifies things o Identifies what is important without worrying too much about the detail - Allows us to manage the complexity of the context or content - Biological Domain o Bioinformatics: Combines different fields of study, including computer sciences, molecular biology, biotechnology, statistics, and engineering Analyse large amount of data: Genomics, Proteomics - Computer Science Manifestations o Pseudocode: An informal description of the steps involved in executing a computer program, often written in something similar to plain [in designed language] - Human Genomes o Structure of cell: Incredibly crowded and incomprehensible for humans o Simplify the representation of cells and make it readable by abstraction (labelling, lettering, shaping, colouring, numbering, etc.) o Formulating in pseudo level can enable us to understand concepts more clearly. o Abstraction simplifies complex life phenomenon to something readable and understandable. - e am : 2. Algorithms - is about following, identifying, using, and creating an ordered set of instructions - ordering things o ascending order (e.g., from 1 to 5, or from A B C to X Y Z) o descending order (e.g., from 5 to 1, or from Z Y X to C B A) - Allows us to order the complexity of the context or content - Biological Domain o Transcription, Translation o Prediction (Gene Function, Protein Function) - Computer Science Manifestations o IF ELSE o Algorithm efficiency 3. Decomposition - Breaking down data, processes, or problems into smaller and more manageable components to solve a problem - Each subproblem can then be examined or solved individually, as they are simpler to work with - Natural way to solve problems - Also known as r to synthesize the final solution - Solve complex problems o If a complex problem is not decomposed, it is much harder to solve at once. Subproblems are usually easy to tackle - Each subproblem can be solved by different parties of analysis - Decomposition forces you to analyse your problem from different aspects - Biological Domain o Biological decomposers (Fungi, Bacteria) - Computer Science Manifestations o Functions o Factorials 4. Pattern Recognition - is about observing patterns, trends and regularities in data - A pattern is a discernible regularity o The elements of a pattern repeat in a predictable manner - In computational thinking, a pattern is the spotted similarities and common differences between problems - It involves finding the similarities or patterns among small, decomposed problems, which can help us solve complex problems more efficiently - Patterns make problems simpler and easy to solve - Problems are easier to solve when they share patterns, we can use the same problem-solving solution wherever the pattern exists - The more patterns we can find, the easier and quicker our problem solving will be - Biological Domain o Gene finding o Biomarkers o Protein synthesis - Computer Science Manifestations o Machine learning o Artificial intelligence o Probability and statistics Module 2: Quantitative Reasoning Quantitative Reasoning Steps to obtain the desired insights - How to frame concrete numerical questions? - How to identify tools and data for analysis? - How to b d models to analyse the data? - How to analyse the results you obtain? Mean - The “average” behaviour of the data points, and is computed as “average” as well - c from entire data distribution Standard deviation - The average deviation of a data point from the Mean of the distribution - Higher SD, wider distribution - -1 ≤ 0 ≤ 1 - Margin of error is narrower/stronger correlation when CORR closer to -1 or 1 - on, the lower the standard error. Too long to read on your phone? Save to read later on your computer Module 3: Cybersecurity Phishing Save to a Studylist - Check who the sender of the email is - Be cautious before clicking on any hyperlinks (T s yourself to ensure you are viewing the actual website) - Look out for the lock icon in the address bar to ensure the website starts with - Report suspicious email to ServiceNow@NTU - lete the email - Do not forward the email to anyone - CIA o y Protect personal information and share only w y o y Practice cyber hygiene and o A: Availability Prevent getting locked out of devices, your actions can affect others Strong Passwords - At least - Contains mber - Contains - Contains upper case letters - Contains lower case letters - Use u n and nonstandard words or create a password from a sentence that makes sense to you - Do not use personal information that people who know you can guess as your password - Use different passwords for different accounts - Change passwords regularly - Use Two Factor Authentication or Multi Factor Authentication ( ) o By enrolling your mobile number or email address to receive a one-time password, or through an authentication app Data Security - Data can exist in both p l and digital forms - Data can belong to an individual or an organization - Levels of Data Security 1. Open: Data distributed to the p c or published on the internet 2. Restrict: Data made a y and (project reports, presentation files) 3. Confidential: Contractually defined as confidential or by nature confidential (personal identifiable information, audit reports) If data is disclosed, target can face statutory penalties cause damage to the organization 4. Classified: Data covered under the Official Secrets Act Unauthorised disclosure leads to damage to national security - L s when leaving desk - Adopt clean desk policy and - Send and store work information through organizational accounts - Keep data storage devices securely - Secure sensitive digital information through encryption Acceptable IT Usage - Use trusted Wi-Fi networks - Avoid doing sensitive transactions - Use BCC instead of CC when sending mass emails to keep the identities confidential, especially when a third party is incolved - Be mindful when connecting external devices to computer as it may contain viruse and malware - Install antivirus software and always ensure it is up to date Cybersecurity in NTU Objectives: - Ensuring Data and Information c d personnel - Integrity: Data and Information held by NTU remains accurate and unmodified by unauthorised personnel - Availability: Data and Information remains usable with sufficient capability to deliver educational services Functions: - The Cyber Security Governance: Responsible for development and e of NTU Cyber security p - The Cyber Security Engineering: Responsible to explore different technologies to hance NTU security capabilities - T m: Manage university (SOC). Operates s to de t and r against NTU Acceptable IT Usage Policy (AIUP): - serves to protect information and IT resources - reduce the risks and damages to the university by governing the usage of all its IT resources (computer, email account, mobile devices, IT services) - Dos o Update your passwords regularly o Always ensure that you keep your password safe o Use the NTU email for all official communications o Use Blind Carbon Copy ( CC) for mass emails o Keep y - DONTs o Don’t share your password with anyone o Don’t forward any University document to your personal email address or online storage that’s not approved by the University o Don’t install software w s o Don’t turn off your anti-virus software or cancel any software updates o Don’t over share information in social media - Good habits o Spot the signs of phishing emails o Use strong passwords o Enable MFA o Secure your sensitive digital information through encryption o Follow the A P and conform to the security bets practices In General P: P ords A: An Virus S: Software Application S: Spot signs of phishing Document continues below Discover more from: Navigating world CC0002 Nanyang… 237 documents Go to course CC0002 Notes P2 100% (13) 58 CC0002 LAMS 96% (26) 23 CC0002 Revision Notes II 9 Navigating 100% (4) world Quiz Revision Navigating 14 100% (1) world CC2 Module 1 Summary 1 Navigating None world CC2 VLM 2 Notes Navigating 2 None world Module 4 – Fake News Falsehoods: A statement is f e or g Misinformation: The inadvertent dissemination of false information n: The intentional dissemination of false information Fake News: A type of falsehood intentionally packaged to look like news to deceive others (intention, format, facticity) - o Attracting clicks o Advertising Revenues - Ideological o Personal Agenda o Weapons of Mass Misinformation - e - News parody - - - Manipulation - What makes people vulnerable? - Sender o Credible or familiar? o Trustworthy or similar? o Proximate or distal? - M ssage o Format o Plausibility - o Trusted or depended on? o Closed or open? o Feedback - Receiver o Confirmation bias o Motivations o Corrections - Context o Information overload o Instability Different Sources - Original Source - Immediate Source - Invisible Source - Trusted Source - Disregarded Source Message characteristics - Plausible? - Mentions Experts? - Conversation Tone - Stirs Emotions - A s (Forwarding the message)? - Channels where information flows o Popularity cues o Reliance o Lack of gatekeeping o Information overload - Higher social media news use= Higher likelihood to believe in fake news - Avoiding news = more likely to believe in misinformation - s: Information that aligns with our existing beliefs Informational apathy (Why people ignore telling people they are wrong about news?) - Issue Relevance: Does not concern me - Interpersonal Relationships: Do not want to offend family/friends - Personal Efficacy: There is no point in reasoning as people already believe Consequences of fake news - Short Term o P l Decis s o Business o Peace and Order o eputation - Long term o Devaluations of Information o Erosion of trust in institutions o ns o What can we do? 1. Individuals Authentication - o The Self: We are old enough to judge and think (experience) o The S e: Is the source reliable o The Message: Check the tone and see if its polemical or deliberately misleading to arouse emotions o The Message Cues: If there are more likes - External Acts of Authentication o Incidental & Interpersonal: By chance discussing with f s o Incidental & Institutional: Waiting for the follow-up news to confirm it o Intentional & Interpersonal: Asking a reliable group to verify o Intentional & Institutional: Googling the information to check - Social process Motivations for authenticating o e (show that you don’t have questionable beliefs) o Group cohesion Strategies of authentication o Group beliefs; “deep stories” o Source affiliation ⁃ Sharing as authenticating Consequences of authentication o Institutionalisation of Interdependence o Ritualisation of collective authentication 2. Governments Authentication - An Act to prevent the electronic communication in Singapore of false statement of fact, to suppress support for and counteract the effects of such communication, to safeguard against the use of online accounts for such communication and for information manipulation, to enable measures to be taken to enhance transparency of online political advertisements, and for related matters. 3. Tech companies Authentication - Intervention (pressure by the public) o Supporting t rs and o Promoting media literacy among users o Reducing financial incentives for content producers o Implementing new features to flag content o ele ost and removing accounts 4. Journalists and fact-checkers - Fact checking o Verification: The process of ev o Fact Checking: The process that occurs post publications - Types of Fact Checkers o Affiliated with news organisation o Government Owned o Independent Organization o Volunteer Groups o In al - Fact Checking Tools o M g o Verify Images o V s o C r - Fact Check Message o V o Rating Scales – demonstrate T or F o Mixed Accuracy Statements o T h (Correc is presented first followed by debunking the f d and then reiterating the correction after) What can we do? 1. Reflect on our own information behaviour. 2. Engage, rather than ignore. 3. Strive to understand others. 4. se and supp eliable and legitimate information sources. 5. Maximise available resources. 6. Equip ourselves. Module 5: Principles of Data Ethics Ethics Ethics is the st y. Morality is a subject that pertains to r - In all human societies on the ethnographic record, people make distinctions between right and wrong (Brown, 1991). - I take it that you have your own views about what is right and wrong. - In the branch of ethics called n s, we try to arrive at well-founded views about morality. Normative ethics relates to using, applying, and developing digital and online tools Why do we need data and digital ethics? There is an international consensus that ethics is vital to the development, application, and use of digital and online technologies (Vallor, 2021). - Technology shapes the way people live. - While digital and online technologies o s (e.g., knowledge, communication, efficiency, personalisation), they a harms to privacy, security, autonomy, fairness, transparency, etc. - Lawmakers are often u ble to keep up with the speed of technological. Hence, not only expert technologists, but also ordinary users, must learn to develop and use technologies in ways that avoids harms while getting the most from the benefits. Moral Theories In normative ethics, moral theories are developed to achieve two aims (Timmons, 2019): T m: To explain what features of actions make them m r Practical aim: To offer practical guidance in making morally correct decisions These three moral theories are among the most influential in normative ethics (Timmons, 2019): 1) U (Jeremy Bentham, John Stuart Mill, Peter Singer, etc.): An action is m t when it would l - b (welfare) as would any other action one might perform instead. Otherwise, the action is wrong. - The classical utilitarians, such as Bentham and Mill, took well-being to consist of e and the absence of pain. - Peter Singer, a contemporary utilitarian, takes wellbeing to consist of the satisfaction of one’s preferences/desires. 2) Virtue ethics (Confucius, Aristotle, etc.): An action is m when it is w o in the circumstances. Otherwise, the action is wrong. - Commonly recognised virtues include h e, b - At is one who has all the virtues. A virtuous person may only be a hypothetical ideal that we can strive to be. 3) Immanuel Kant’s deontological ethics: An action is m when it t persons (including oneself) s and n s. Otherwise, the action is wrong. - Kant’s theory says that all persons are unconditionally valuable insofar as they are rati al and a nomous. - It also says that we should respect the value of persons, and not use them in a Principles of Data Ethics Moral theories are meant to provide very general explanations and e concerning what we morally ought to do. While moral theories have the advantage of comprehensiveness, it can be o what they would prescribe in a particular context. Several professional associations and private firms have formulated more specific principles to guide actions with respect to data and information technology. - Links to these sets of principles are provided in the Notes section below. The following principles are sampled from the Singapore Computer Society’s professional Code of Conduct: SCS members will act at all times with integrity. They will: - not lay claim to a level of competence that they do not possess - act with n when entrusted with confidential information - be impartial when ng advice and will disclose any relevant personal interests - give c e by others where credit is due SCS members will act with professionalism to enhance the prestige of the profession and the Society. They will: - u hold and im s of the Society through n in their formulation, establishment, and enforcement - e to the - not speak on behalf of the Society - n n of any other person - use their special knowledge and for the advancement of human welfare Cyberbullying Cyberbullying is the use of the internet or digital devices to inflict psychological harm p (Quinn, 2019; Media Literacy Council 2018). Examples: - Repeatedly texting or emailing hurtful messages to another person. - Spreading derogatory lies about another person. - Tricking someone into revealing highly personal information. - “Outing” or revealing someone’s secrets online. - Posting embarrassing photographs or videos of other people without their consent. - Impersonating someone else online in order to damage that person’s reputation. - Threatening or creating significant fear in another person. Prevalence: - According to the 2020 Child Online Safety Index (Cosi) report, which includes data on 145,000 children across 30 countries, experienced cyberbullying, either as the bullies or as the victims. - Within Singapore, and s were exposed to cyberbullying. Effects: - Depression and anxiety - Low self-esteem - Difficulty sleeping - Headaches, stomach aches - Suicidal thoughts - Suicide attempts - Eating disorders What you can do if you are cyberbullied: - Don’t blame yourself. - Don’t retaliate. - Save the evidence: Take screenshots of texts. - Talk to someone you trust. - Block the bully. - Report the bully. - Keep social media passwords private. - Restrict others’ access to your social media pages. - Change your social media accounts: If you are harassed, delete the account and create a new one. How to know if someone you care about is being cyberbullied: - Changes in mood or personality. - Work or school performance declines. - Lack of desire to do things they normally enjoy. - Upset after using phone or going online. - Secretive about what they are doing online. - Unusual online behaviour: Not using phone/computer at all; using phone/computer all the time; receiving lots of notifications. - Deleting social media accounts. Digital and online technologies have a major impact on one’s ability to secure cy. In particular, these technologies affect what the philosopher Anita L. Allen describes as informational privacy: “confidentiality, anonymity, data protection, and secrecy of facts about persons” (Allen, 2005) Consider this incident where some researchers released the personal profile details of 70,000 users on OkCupid, a dating website: Brian Resnick, “Researchers just released profile data on 70,000 OkCupid users without permission,” Vox (12 May 2016). Critics maintained that the (informational) privacy of the OkCupid users was violated by the researchers, because the researchers stored and re-deployed the personal A right to privacy is recognised in all s instruments, including A 2 the Universal Declaration of Human Rights: In l it can be d al or - Law enforcement and regulators are not able to constantly monitor the internal operations of organisations. Such constant surveillance isn’t even desirable. - Leadership within the organisation may cover up any corrupt activities. There are many examples of misconduct in organisations e, or o - The 1986 Challenger Disaster is a memorable case where something catastrophic happened as a result of internal mismanagement. - A more recent case involving Wirecard, an electronic payment company, was reported in Singapore. - Data analytics firm Cambridge Analytica crossed many ethical lines. Sometimes it is up to ordinary, low-level people to “blow the whistle” on “A whistle is someone who breaks ranks with an organization in order to n about a r attempts to report the concerns through authorized organizational channels have buffed.” (Quinn, 2019, emphasis added) - The question of whether to “blow the whistle” can arise in any organisation— not just in s and - NTU has its own dedicated whistle-blower channel, which is taken very seriously But when should one whistle-blow? In his well-known textbook on business ethics, Richard T. De George proposed that whistle-blowing is morally permissible when three conditions are fulfilled (De George, 2006; Brenkert, 2009): 1. The firm…will do [or has done] serious and considerable harm to employees or to the pub. 2. Once employees ct or to the g , they should re or and make their n. 3. If one's immediate supervisor d e about the concern or complaint, the e De George went on to suggest that if t et, then it would be m y for someone to whistle-blow (De George, 2006; Brenkert, 2009): 4. The whistle‐blower must have, or have accessible, documented evidence that would c r that one's view of the situation is c and 5. The employee must have good reasons to believe that by going public the The ul must be and the d First objection to De George’s criteria (Quinn, 2019): The criteria are to t. It can be m e to whistle-blow, through 3 are met. - For instance, it may be morally permissible to whistle-blow when you know that c, but there is not enough time to lobby s ors and exhaust all internal reporting procedures. - By itself, the effort to prevent serious harm may be enough to make whistle- Second objection to De George’s criteria (Quinn, 2019): The c. It can be morally obligatory to whistle-blow e n conditions 4 and 5 have not be fulfilled. - For instance, a single employee m 3, but still be unable to acquire enough documented evidence to convince an impartial observer that any wrongdoing has been done. - However, it may s w, if one is confident that another organisation, such as law enforcement or the media, would be e to p ation’s wrongdoing. Module 6: IP and Rights Licensing Intellectual Property (IP) Creations resulting from the exercise of the human brain - Examples include inventions, designs, ideas, plant hybrids, music, poems, paintings, photographs, logos, books, films, cartoon characters, trade secrets. B s, i.e., intellectual property rights (IPRs) IP law recognises that creators have the right to protect their work. - IP law gives legal rights to IP creators, allowing them to use of their IP for a specific period of time. Different Types of IP Copyright - and r - Written, drawn, composed (books, movies, songs) - o Patents - that p m (cars, TV, mobile phones) - Signs used in b s to d es from competitors (logos) - c and v (concepts, trade secrets, personal information/data) Others - Registered designs - Plant varieties - Geographical indications - Layout design of an integrated circuit Why protect IP? Provides m n for creators - As recognition, protection of in Encourages constant creation and innovation Allows creators to exploit their works for commercial gain Allows creators to de nt (wrongful use of IP) What is Copyright? © Copyright is the m in which a s, for example in a: - Short story, musical composition, theatre script, painting, computer programme, photograph, movie, or video game It can be described as a b - Allows owners to enforce their rights against infringement Singapore’s copyright law is governed by the Copyright Act Copyright protects the “form” of an idea and NOT the idea itself No need for novelty so long as there is independent creation. t is n to attach to a work— Symbol act as a notice to let people know - s - w - ability to find out if the work is still in protection Criteria for protection Copyright protection a w, so long as certain basic criteria are satisfied: Fixed in tangible form (written/graphic form, capable of being perceived) - Work was created independently by the author Author/creator is a How does Copyright protect? Form of expression, and not the idea or information itself. or i n is protected by d. Many different m d. Expression must, as a general rule, be original. (official stamps). Copyright arises “as soon as the ink dries”. Unprotected Matter I s and concepts D (a research finding) (steps in applying for a grant) Methods (solution to a problem) Any subject matter that has not been reduced to a tangible form Works in the p n - Conceptual space where intellectual property has exhausted its protection duration reside - Use w - NOT the internet Duration of Protection Literary, dramatic, musical, Life of author plus 70 years from the end of the year in and artistic works which the author died Published editions rs from the end of the year in which the edition was first published Sound recordings and films 70 years from the end of the year of release Broadcasts and cable 5 programmes Performances 7 Overlapping Copyright One product may contain a variety of copyright works t (e.g., purchasing an original music CD does not give right to make copies) Person who c from the moment of creation Except: - t: If the work is created by an employee pursuant to the terms of his nt, the - B t: The author can agree to transfer some or all of his rights. : - Where work is created jointly by more than one author, the authors are all co- s of the copyright in the work - Concept: Where more than one author creates inseparable or interdependent k E.g., two trainers involved in creating the training materials for a course - Requirement: ,n o What is a C ? Definition of a contract: “An agreement giving rise to obligations which are enforced or recognised by law” It is a v t between s. The law exists to g and re he parties’ relationship in such agreements. It can be v or d. - Written contract - Done because humans t especially when it consists of many things to be done - To be - e of an agreement - W d from party in carrying out/performing obligation in terms of quality/standard of performance - By when these are to be performed - Can be time-consuming, troublesome, inefficient Every time we undertake a t n – engage in formation of contract Functions of Contracts I y and and obligations Allocate risk (between parties) - Ensure that all f. For instance, breaching of contract (party omits to fulfil a contract obligation), contract would have stated what needs to be done to repair the breach Provide certain guarantees Set performance standards Provide how non-fulfilment of obligations should be dealt with What the Law of Contract Covers Formation of contracts - Elements required for a contract to exist (terms) of a contract of the contract by its parties Remedies when there is n fulfilment of either party’s obligations (breach) Elements of a Contract - Indication by offeror of willingness to contract Acceptance - Absolute and unqualified—must be c - Usually indicated by e or the carrying out of an act in return for the b Intention to create legal relations - Reasonable to conclude from conduct of parties of their intention to be legally b d Capacity - Parties must have the c - Issue of minors (below age of 18) and im Once all these elements are in place, a contract is deemed to be FORMED. of these means that no contract is in existence. Contractual Terms and Performance Set out and determine the r s Provide for how obligations are to be performed Provide for how risks are to be allocated Provide for h - How it begins, carries on, ends, or is renewed Common Terms in Contracts P e of contract/description of collaboration - What is the aim of the contract? - How much and how is payment to be made? s and o - How long is the contractual relationship going to last? How will the contract end? (fundamental promises) - Basic assurance that the contract can be carried out effectively D n - How will disagreements be resolved? Breach and Remedies Contract is breached when there is non-performance of a term. Breach entitles the wronged party to demand cure of the breach from the other party, as well as financial compensation (damages) if there is loss. (remedies) - May also be entitled to terminate contract Using Contracts with IP You already have an understanding of the law of contract. You now have a general understanding of IP, and copyright. Contracts combined with IP enables you to transact/deal with IP usage. Words you need to be familiar with: Permission, release, licence, assignment, clearance Dealing with IP The law regards intellectual property as a type of IP is capable of being owned and dealt with as other types of personal property. In other words, you can buy, sell, lease/hire out, or give away IP. It has commercial value. Two KEY methods that are used in dealing with IP: Licence (noun) License (verb) A licence is a type of contract that gives permission to the holder/recipient to c , which would be A licence gives the owner the ability to use or exploit intellectual property y, most commonly requiring a fee in return for the grant of the licence. Types and Uses: - Granted to more than one person e - Granted to o y Where do you see licences being used? - All s - All SaaS platforms - All media aggregation platforms where Assign (verb) An assignment is another type of contract - Legal meaning of “assign”: To regard as belonging to - Must be in writing and signed by or on behalf of the assignor Means by which a person Legal Effect Under the assignment, the (person the assignment) ts that are the s nt to the e (the person r g these rights). The assignee is now the new owner of the property. Licensing Assignment Grants someone else (other than the IP Transfers the entire title and interest in owner) the right someone’s IP to another Le s costly More costly IP owner remains in control IP owner gives up control Use an IP already created by someone else Wish to have complete control over for a s n u by someone Note: The way a licence is worded can make it almost as strong or effective as an assignment. Thus, it is important to understand the language used in licences and assignment agreements Module 7a: Artificial Intelligence AI Present Day Renaissance : Become widely available, such as C : Availability of large amount of data due to M g Deep Learning (most popular) Implementation of ML based on Deep Neural Network that Artificial Neural Network ( ) - Classifying n Convolution Neural Network ( ) - Classifying images Recurrent Neural Network ( ) - Time series data (e.g., audio) Deep Reinforcement Learning Basis: AlexNet N k H - Consists of (with large amount of data) - The ‘algorithm’ that can learn and improve by itself Mimics the human brain to recognize pattern - Ability to learn Deep Neural Network - Multiple layers of hidden layers - Much algorithms can be learnt AlexNet At the 2012 ImageNet computer image recognition competition: Alex Krizhevsky used machine to im algorithm (CNN). First time that machine learning based algorithm beat, by a huge margin, handcrafted software written by computer vision domain experts. n but detect that there is a person in front of the camera (e.g., during online quiz) AI Applications R s Autonomous Automotive and Navigation - Via sensors, images - Reduce human errors, running cost (predict when to do maintenance, prevent malfunction) - Improve convenience, safety - Navigation: optimal routes, avoid ERP S - Recommender, advertisement s - Smartphone with AI-driven apps such as Siri, Google Assistant, Alexa, Cortana - Smart household devices such as TV, refrigerators, ovens - Smart Floor vacuum cleaners - Smart security camera - Inventory management (reduce cost) - Demand forecasting (improve efficiency) - Personalised merchandising (preference, interest, browsing history) - Chatbots - Improve customer experience e - Better business analytics (accuracy, high volume of data) - Algorithm trading (execute trades at optimal prices) - Credit risks assessment - Wealth management (automated portfolio manager) - Fraud - Analyse medical images - Early detection (cancer) - Develop new drugs - Genomic profiling - Nutrient and water management - Detect pests and diseases in plants - Detect weeds - Analyse crop health (by drones) - Improve harvest quality and accuracy E n - Improve teaching and learning strategies - AL e-tutors - Automatic grading - AI based e-proctoring AI concerns s M I (Deepfake: spread false information, create tension) AI explainability s (depends on type of data) g (weapon) Summary AI is rapidly transforming the way we live: - Helps to makes things run more efficiently - Improves safety and work productivity - n to do s - Enables Current generation of AI technologies are still considered as arrow Intelligence (ANI) - Goal is to eventually a But there are also many concerns about the potential risk that we need to be aware of - Responsible AI Module 7b: Blockchain and its Application in Finance Barter Economy: to trade something you have for something you don’t use c t (cocoa beans) disadvantage – depends on size, shelf-life Money/Currency: according to mainstream economics, money (currency)r ng ng as it is a that can be readily used by anyone allow s as sellers have an with whom they want to do business with o a seller can simply sell his or her goods and in turn pay their trading partners with the money earned much easier to bring currency around as compared to bringing bags of cocoa beans coins and papers l er than most commodities used for trading can be a d Egyptians invented minted currency o Use metal rings as money o Then made coins from precious metals such as gold, silver, or copper o Metallic coins are heavy to carry for daily transactions Paper money was invented o Individuals would deposit their coins with a trustworthy party and receive a note denoting how much coins they had deposited o The note could then be redeemed for currency at a later date. Central Bank – key concept of modern money o paper money is a c cy that is d and a o the country’s central bank that authorises and regulates the printing of paper mo , ensuring that the f y o Paper money d and later on government-issued currency is purely based on a country's government, so called o The r of the fiat money, and the nt, d y In 20th century, cheque becomes a very popular non-cash method for making payments. o A cheque is a document that o from a person's account to the person in whose name the cheque has been issued. o Can still issue even if the account has insufficient money! o The person r, has a banking account where the money is held. Say for example, person 1 issues a cheque to person2. When person2 drop cheque at the deposit box, person 2's bank will send the relevant information to person 1's bank. After person1's bank check that the cheque is valid and person 1 has enough money in his account, person1's bank will transfer the money to person2's bank account. Advantages of cheque Disadvantages of cheque It is m Cheques are r; n amount of cash around. refuse to accept them. Cheques are than cash when carrying Cheques are ess if drawer has no them around since a thief can’t do much enough funds in their account. with your cheque book. They can be There is a o drawing a cheque. They can be Credit Card o card issuer creates a bank account for the cardholder, from which the cardholder can y (with a limit) for t or as a cash advance o t or m has become the main tool to transact in our everyday life o generally do not carry cash, cheques or credit cards around nowadays. We simply use our mobile phone to make a payment Bitcoin type of cryptocurrency an example of blockchain application Bitcoin price: (exchange rate between bitcoin and money) o s o has a f y o value of bitcoin fl d in the market Bitcoin wallet: Important part: - s (long string of letters and numbers) - e (contains same info, scanned by camera) Sending bitcoin, screen is presented with: 1. A d. 2. The a d, in b n (BTC) or his l (USD). She can then use (spend) the change output in a subsequent transaction. This is called the UXTO unspent transaction output. The transactions will be recorded on the bitcoin blockchain. The transaction ledger can be checked by anybody through various bitcoin explorer. The screenshot on the right is one example. Alice’s wallet application contains all the logic for selecting appropriate inputs and outputs to build a transaction to Alice’s specification. At Bob’s café, Alice only needs o t, and the rest happens in the wallet application without her seeing the details. Alice’s funds are in the form of a 0.10 BTC output, which is too much money for the 0.015 BTC cup of coffee. Alice will need 0.845 BTC in change. 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1DQ\DQJ7HFKQRORJLFDO8QLYHUVLW\6LQJDSRUH$OO5LJKWV5HVHUYHG EĞǆƚǁĞůůůŽŽŬĂƚƚŚĞŚĂƐŚǀĂůƵĞŽĨĂďůŽĐŬŝŶdŝŵƉůĞŵĞŶƚĂƚŝŽŶǁŚŝĐŚŝƐƚŚĞ ŝĚĞŶƚŝƚǇŽĨƚŚĞďůŽĐŬEŽƚĞƚŚĂƚŽƚŚĞƌŝŵƉůĞŵĞŶƚĂƚŝŽŶƐ;ƐƵĐŚĂƐdͿŵŝŐŚƚƵƐĞŽƚŚĞƌ ŵĞƚŚŽĚƐƚŽĂĐŚŝĞǀĞƐŝŵŝůĂƌŽƵƚĐŽŵĞƐ dŚĞďůŽĐŬŚĞĂĚĞƌŝƐĐƌĞĂƚĞĚǁŝƚŚƐŝǆĨŝĞůĚƐ ϭ sĞƌƐŝŽŶŶƵŵďĞƌ Ϯ ,ĂƐŚŽĨƚŚĞƉƌĞǀŝŽƵƐďůŽĐŬ ϯ dŝŵĞƐƚĂŵƉ ϰ ŝĨĨŝĐƵůƚǇ ϱ DĞƌŬůĞƌŽŽƚĐŽŵƉƵƚĞĚŝŶƚŚĞƉƌĞǀŝŽƵƐƐƚĞƉ EŽƚĞ DĞƌŬůĞƌŽŽƚŝƐĐƌĞĂƚĞĚďǇŚĂƐŚŝŶŐƚŽŐĞƚŚĞƌƉĂŝƌƐŽĨdƌĂŶƐĂĐƚŝŽŶ/ƐǁŚŝĐŚŐŝǀĞƐǇŽƵ ĂƐŚŽƌƚǇĞƚƵŶŝƋƵĞĨŝŶŐĞƌƉƌŝŶƚĨŽƌĂůůƚŚĞƚƌĂŶƐĂĐƚŝŽŶƐŝŶĂďůŽĐŬ ,ĞŝŐŚƚŝƐƐŝŵƉůǇƚŚĞƐĞƌŝĂůŶƵŵďĞƌŽĨƚŚĞďůŽĐŬǁŚĞƌĞĨŝƌƐƚďůŽĐŬŝƐϭĂŶĚƐŽŽŶ ŝĨĨŝĐƵůƚǇŝƐĂŵĞĂƐƵƌĞŽĨŚŽǁŚĂƌĚŝƚŝƐƚŽĨŝŶĚĂǀĂůŝĚďůŽĐŬƚŽŵŝŶĞ&ŽƌĞǆĂŵƉůĞŝĨĂ ƉƌĞǀŝŽƵƐďůŽĐŬŝƐŵŝŶĞĚŝŶůĞƐƐƚŚĂŶϭϬŵŝŶƵƚĞƐƚŚĞŶƚŚĞŶĞǆƚďůŽĐŬǁŽƵůĚďĞ ϯϮ ƚĂƌŐĞƚĞĚĂƚŵŽƌĞƚŚĂŶϭϬŵŝŶƵƚĞƐƚŽďĞŵŝŶĞĚďǇŝŶĐƌĞĂƐŝŶŐƚŚĞŶƵŵďĞƌŽĨďŝƚƐĂƐĂ ƉĂƐƐǁŽƌĚĂŶĚƐŽŽŶdƚĂƌŐĞƚƐϭďůŽĐŬƚŽďĞŵŝŶĞĚĞǀĞƌǇϭϬŵŝŶƵƚĞƐ ϯϮ 6WHS+DVKWKH&XUUHQW%ORFN+HDGHU %ORFN%ORFN  1DQ\DQJ7HFKQRORJLFDO8QLYHUVLW\6LQJDSRUH$OO5LJKWV5HVHUYHG dŚĞďůŽĐŬŚĞĂĚĞƌ;ǁŚŝĐŚĐŽŶƚĂŝŶƐƚŚĞDĞƌŬůĞƌŽŽƚͿŝƐŚĂƐŚĞĚƌĞƐƵůƚŝŶŐŝŶƚŚĞďůŽĐŬ ŚĂƐŚ ϯϯ 6WHS+DVK9DOXHVLQ6WHSVDQG +DVKDDQGE  1DQ\DQJ7HFKQRORJLFDO8QLYHUVLW\6LQJDSRUH$OO5LJKWV5HVHUYHG ϯϰ 0HUNOH5RRW 0HUNOH5RRW +$%&' +DVK+$%+&' +$% +&' +DVK+$+% +DVK+&+' +$ +% +& +' +DVK7[$ +DVK7[% +DVK7[& +DVK7['  1DQ\DQJ7HFKQRORJLFDO8QLYHUVLW\6LQJDSRUH$OO5LJKWV5HVHUYHG DĞƌŬůĞZŽŽƚ ĂĐŚďůŽĐŬŝŶƚŚĞďŝƚĐŽŝŶďůŽĐŬĐŚĂŝŶĐŽŶƚĂŝŶƐĂƐƵŵŵĂƌǇŽĨĂůůƚŚĞƚƌĂŶƐĂĐƚŝŽŶƐŝŶƚŚĞ ďůŽĐŬƵƐŝŶŐĂDĞƌŬůĞƚƌĞĞDĞƌŬůĞƚƌĞĞĂůƐŽŬŶŽǁŶĂƐĂďŝŶĂƌǇŚĂƐŚƚƌĞĞŝƐĂĚĂƚĂ ƐƚƌƵĐƚƵƌĞƵƐĞĚĨŽƌĞĨĨŝĐ ĞŶƚůǇƐƵŵŵĂƌŝƐŝŶŐ ĂŶĚǀĞƌŝĨǇŝŶŐƚŚĞŝŶƚĞŐƌŝƚǇŽĨůĂƌŐĞƐĞƚƐŽĨ ĚĂƚĂDĞƌŬůĞƚƌĞĞƐĂƌĞďŝŶĂƌǇƚƌĞĞƐĐŽŶƚĂŝŶŝŶŐĐƌǇƉƚŽŐƌĂƉŚŝĐŚĂƐŚĞƐ DĞƌŬůĞƚƌĞĞŝƐĐŽŶƐƚƌƵĐƚĞĚďǇƌĞĐƵƌƐŝǀĞůǇŚĂƐŚŝŶŐƉĂŝƌƐŽĨŶŽĚĞƐƵŶƚŝůƚŚĞƌĞŝƐŽŶůǇ ŽŶĞŚĂƐŚĐĂůůĞĚƚŚĞƌŽŽƚŽƌDĞƌŬůĞƌŽŽƚ ϯϱ +HUHLVWKH0HUNOHURRW  1DQ\DQJ7HFKQRORJLFDO8QLYHUVLW\6LQJDSRUH$OO5LJKWV5HV ϯϲ :KDW0DNHVWKH%LWFRLQ%ORFNFKDLQ6DIH" ĨƚĞƌƚŚĞĚŝƐĐƵƐƐŝŽŶŽŶƚŚĞƌĞĂůͲůŝĨĞƵƐĞĐĂƐĞůĞƚΖƐĚŝƐĐƵƐƐƐĞǀĞƌĂůƋƵĞƐƚŝŽŶƐ &ŝƌƐƚǁŚĂƚŵĂŬĞƐƚŚĞďŝƚĐŽŝŶďůŽĐŬĐŚĂŝŶƐĂĨĞ tĞůůƚŚĞĐƌǇƉƚŽŐƌĂƉŚŝĐƐǇƐƚĞŵŵĂŬĞƐƚƌĂŶƐĂĐƚŝŽŶƐŝƌƌĞǀĞƌƐŝďůĞǁŚŝĐŚŵĞĂŶƐŽŶĐĞĂ ďůŽĐŬŝƐĐƌĞ ŝƚĐ zŽƵĐĂŶŚŽǁĞǀĞƌĐĂŶĂĚĚ ŝŶĨŽƌŵĂƚŝŽŶƚŽŝƚdŚŝƐ ƌĞƐƚƌŝĐƚƐƉĞŽƉůĞĨƌŽŵƌĞǀĞƌƐŝŶŐĂŶǇƚƌĂŶƐĂĐƚŝŽŶƚŚĂƚŚĂƐĂůƌĞĂĚǇ ƚĂŬĞŶƉůĂĐĞ ϯϳ :KDW0DNHVWKH%LWFRLQ%ORFNFKDLQ6DIH" ^ĞĐŽŶĚƚŚĞďŝƚĐŽŝŶďůŽĐŬĐŚĂŝŶŝƐƉƵďůŝĐǁŚŝĐŚŵĂǇŵĂŬĞŝƚƐĞĞŵƵŶƐĂĨĞͶďƵƚŝŶƚŚĞ ĐĂƐĞŽĨďŝƚĐŽŝŶŝƚŚĞůƉƐƚŽŵĂŬĞŝƚƐĂĨĞĞƐƉŝƚĞƚŚĞĂŶŽŶǇŵŝƚǇŽĨƚŚĞƵƐĞƌĂůů ƚƌĂŶƐĂĐƚŝŽŶƐŽŶƚŚĞŶĞƚǁŽƌŬĂƌĞĂĐĐĞƐƐŝďůĞƚŽƚŚĞƉƵďůŝĐŵĂŬŝŶŐŝƚĚŝĨĨŝĐƵůƚƚŽŚĂĐŬŽƌ ĐŚĞĂƚƚŚĞƐǇƐƚĞŵ &ŝŶĂůůǇƚŚĞĚĞĐĞŶƚƌĂůŝǌĂƚŝŽŶĐŽŶƚƌŝďƵƚĞƚŽƚŚĞƐĞĐƵƌŝƚǇĂƐǁĞůůdŚĞďŝƚĐŽŝŶŶĞƚǁŽƌŬŝƐ ĚŝƐƚƌŝďƵƚĞĚ ĚƚŚĂƚŬĞĞƉƚƌĂĐŬŽĨĂůů ƚƌĂŶƐĂĐƚŝŽŶƐŚĂƉƉĞŶŝŶŐŽŶƚŚĞƐǇƐƚĞŵdŚŝƐĞŶƐƵƌĞƐƚŚĂƚŝŶĐĂƐĞƐŽŵĞƚŚŝŶŐŐŽĞƐ ǁƌŽŶŐŽŶŽŶĞƐĞƌǀĞƌƚŚĞƌĞĂƌĞŽƚŚĞƌƐƚŽďĂĐŬƵƉdŚŝƐŵĂŬĞƐŝƚŵĞĂŶŝŶŐůĞƐƐƚŽŚĂĐŬ ĂŶǇŽŶĞƐĞƌǀĞƌ ϯϴ 6R:KDW¶VWKH%LJ'HDO$ERXW%LWFRLQ" ^ŽǁŚĂƚƐƚŚĞďŝŐĚĞĂůĂďŽƵƚďŝƚĐŽŝŶEŽ/ĚŽŶƚŵĞĂŶƚŚĞƉƌŝĐĞ/ŵĞĂŶŚŽǁĚŽĞƐ ƚŚĂƚŚĞůƉƚŚĞƐŽĐŝĞƚǇ /ĨǇŽƵǁĂŶƚƚŽƚƌĂĚĞďŝƚĐŽŝŶƚŚĞůŽǁĞƐƚƵŶŝƚǇŽƵĐĂŶƚƌĂĚĞŝƐĐĂůůĞĚ^ĂƚŽƐŚŝǁŚŝĐŚŝƐ ƚŚĞŶĂŵĞŽĨŝƚƐĨŽƵŶĚĞƌ^ĂƚŽƐŚŝEĂŬĂŵŽƚŽϭƵŶŝƚŽĨďŝƚĐŽŝŶŝƐĞƋƵŝǀĂůĞŶƚƚŽϭϬϬ ŵŝůůŝŽŶ^ĂƚŽƐŚŝƐƐƵŵĞĂďŝƚĐŽŝŶŝƐǁŽƌƚŚϰϮϱϬϬ^'ŶŽǁĂƵŶŝƚŽĨ^ĂƚŽƐŚŝǁŝůůďĞ ǁŽƌƚŚϬϬϬϬϰϮϱ^'ϭ^'ǁŝůůŐŝǀĞǇŽƵĂďŽƵƚϮϯϱϯƵŶŝƚƐŽĨ^ĂƚŽƐŚŝ ϯϵ 6R:KDW¶VWKH%LJ'HDO$ERXW%LWFRLQ" /ĨǇŽƵŐŽĂŶĚďƵǇĂĐŽĨĨĞĞƚŚĂƚĐŽƐƚƐϭ^'ƚŽĚĂǇǇŽƵĐĂŶƵƐĞĐĂƐŚĐƌĞĚŝƚĐĂƌĚŽƌŽŶĞ ŽĨƚŚĞŵŽƐƚƉŽƉƵůĂƌŝŶƐƚĂŶƚƉĂǇŵĞŶƚƐǇƐƚĞŵƐ WĂǇEŽǁ WĂǇEŽǁ ŝƐĞĂƐǇƚŽƵƐĞĂŶĚ ǇŽƵũƵƐƚŶĞĞĚƚŽŚĂǀĞǇŽƵƌƉŚŽŶĞĂŶĚŶŽƚŚĂǀĞƚŽǁŽƌƌǇĂďŽƵƚĐĂƌƌǇŝŶŐǇŽƵƌǁĂůůĞƚ ĂƌŽƵŶĚ/ŵĂŐŝŶĞƉĂǇŝŶŐĨŽƌƚŚĞĐƵƉŽĨĐŽĨĨĞĞǁŝƚŚϮϯϱϯƵŶŝƚƐŽĨ^ĂƚŽƐŚŝƵƐŝŶŐ Ă WĂǇEŽǁ ĞƋƵŝǀĂůĞŶƚƐǇƐƚĞŵƐŽĨƚŚĞĐƵƌƌĞŶƚŵŽŵĞŶƚǁĞĚŽŶƚŚĂǀĞƐƵĐŚĂ ƐǇƐƚĞŵ &ŽƌĐŽŶǀĞŶŝĞŶĐĞƐĂŬĞůĞƚƐŝŵĂŐŝŶĞĂƚĞƌŵĂŶĚĐĂůůŝƚ ^ĂƚŽƐŚŝEŽǁ^ŽǇŽƵŐŽ ĂŶĚďƵǇĂĐƵƉŽĨĐŽĨĨĞĞƵƐŝŶŐ ^ĂƚŽƐŚŝEŽǁzŽƵŵŝŐŚƚƚŚŝŶŬĞƌŵǁŚǇĚŽ/ďŽƚŚĞƌ ƐŝŶĐĞ/ĂůƌĞĂĚǇŚĂǀĞ WĂǇEŽǁ ϰϬ :K\6KRXOG,%RWKHU" zŽƵĂƌĞĐŽƌƌĞĐƚzŽƵĚŽŶƚŚĂǀĞƚŽďŽƚŚĞƌƵƚŝĨǇŽƵĂƌĞƚƌĂǀĞůůŝŶŐŽǀĞƌƐĞĂƐĨŽƌĂ ŚŽůŝĚĂǇĨŽƌĞǆĂŵƉůĞǀŝƐŝƚŝŶŐ^ĞŽƵůĂŶĚĐŚĞĐŬŝŶŐŽƵƚŝƚƐŝĐŽŶŝĐŽďƐĞƌǀĂƚŝŽŶƚŽǁĞƌŽƌ ^ǁŝƚǌĞƌůĂŶĚĨŽƌŝƚƐĨĂŵŽƵƐĂŶĚďĞĂƵƚŝĨƵůŚĂƉĞůƌŝĚŐĞĂŶĚǇŽƵǁĂŶƚĞĚƚŽďƵǇĂĐƵƉ ŽĨĐŽĨĨĞĞtŚĂƚĚŽǇŽƵĚŽzŽƵĚĞŝƚŚĞƌŚĂǀĞŐŽŶĞƚŽĂŵŽŶĞǇĐŚĂŶŐĞƌƚŽŐĞƚƚŚĞ ůŽĐĂůĐƵƌƌĞŶĐǇǁŝƚŚƚŚĞƌŝƐŬŽĨƵŶĚĞƌŽƌŽǀĞƌƐƉĞŶĚŝŶŐďĞĨŽƌĞƚŚĞƚƌŝƉŽƌǇŽƵĐĂŶƐŽůǀĞ ƚŚĂƚŝƐƐƵĞďǇƉĂǇŝŶŐǁŝƚŚĂĐƌĞĚŝƚĐĂƌĚǁŚŝĐŚƵƐƵĂůůǇŚĂƐŚŝŐŚůǇƵŶĨĂǀŽƵƌĂďůĞ ĞǆĐŚĂŶŐĞƌĂƚĞŝƚŚĞƌǁĂǇƉƵƚƐǇŽƵĂƚĂůŽƐŝŶŐĞŶĚ EŽǁŝŵĂŐŝŶĞƚŚĞǁŚŽůĞǁŽƌůĚŝƐĂĐĐĞƉƚŝŶŐďŝƚĐŽŝŶĂŶĚŝƚƐĞƋƵŝǀĂůĞŶƚƐƵďƵŶŝƚƐ^ĂƚŽƐŚŝ ĂŶĚǇŽƵŚĂǀĞ^ĂƚŽƐŚŝEŽǁ ĂƉƉŽŶǇŽƵƌƉŚŽŶĞzŽƵǁĂŶƚƚŽŐŽĨŽƌŚŽůŝĚĂǇƚŽŵŽƌƌŽǁ zŽƵůůũƵƐƚŶĞĞĚƚŽďŽŽŬĂƚŝĐŬĞƚĂŶĚƉĂĐŬǇŽƵƌůƵŐŐĂŐĞ ϰϭ ,V,W-XVWIRUWKH )LQDQFH,QGXVWU\" /ƐŝƚũƵƐƚĨŽƌƚŚĞĨŝŶĂŶĐĞŝŶĚƵƐƚƌǇdŚĞƌĞĂƌĞĚĞĨŝŶŝƚĞůǇŵŽƌĞƉŽƐƐŝďŝůŝƚŝĞƐ/ŵĂŐŝŶĞŽŶĞ ĚĂǇƐŽŵĞŽŶĞĐƌĞĂƚĞƐĂƌĞůŝĂďůĞŽǀŝĚͲϭϵƚĞƐƚĂƉƉƚŚĂƚĐĂŶƐĞĐƵƌĞůǇŝĚĞŶƚŝĨǇǇŽƵĂƐ ƚŚĞŽŶĞďĞŝŶŐƚĞƐƚĞĚĂŶĚĂƚƚŚĞƐĂŵĞƚŝŵĞůŝŶŬƚŚĞƌĞƐƵůƚǁŝƚŚŝƚĨƚĞƌǁŚŝĐŚƚŚŝƐ ŝŶĨŽƌŵĂƚŝŽŶŝƐƉƌŽƉĂŐĂƚĞĚƚŚƌŽƵŐŚŽƵƚƚŚĞǁŽƌůĚƵƐŝŶŐďůŽĐŬĐŚĂŝŶƚĞĐŚŶŽůŽŐǇzŽƵ ǁŽŶƚŚĂǀĞƚŽŐŽƚŽƚŚĞĚŽĐƚŽƌĨŽƌĂŽǀŝĚƉŽƐŝƚŝǀĞŽƌŶĞŐĂƚŝǀĞĐĞƌƚŝĨŝĐĂƚŝŽŶǁŚĞŶǇŽƵ ƚƌĂǀĞů ϰϮ ,V,W-XVWIRUWKH )LQDQFH,QGXVWU\" KŶĐĞƚŚĞƉůĂƚĨŽƌŵŝƐĂǀĂŝůĂďůĞǇŽƵĐĂŶƐŝŵƉůǇǁĂůŬŝŶƚŽĂŵĂůůĂŶĚƚƌĂǀĞůŽŶĂĨůŝŐŚƚ ǁŝƚŚƚŚĞƐĞĐƵƌĞĂƉƉŶĚŝĨǁŚĂƚŝĨƚŚĞŝŵƉůĞŵĞŶƚĂƚŝŽŶŽĨƚŚŝƐƚĞĐŚŶŽůŽŐǇŝƐǇŽƵ ^ƚĂǇƚƵŶĞĚĨŽƌƚŚĞŵŽƌĞĚŝƐĐƵƐƐŝŽŶŽŶďůŽĐŬĐŚĂŝŶŝŶŽƚŚĞƌĐŽƵƌƐĞƐtĞĂƌĞĞǆƉĞĐƚŝŶŐ ǇŽƵƌďŝŐŝŶǀĞŶƚŝŽŶ ,ĞƌĞďƌŝŶŐƐƚŽƚŚĞĞŶĚŽĨ ŵǇƉƌĞƐĞŶƚĂƚŝŽŶĨŽƌƚŚŝƐŵŽĚƵůĞ,ŽƉĞǇŽƵĞŶũŽǇĞĚĂŶĚ ƚŚĂŶŬǇŽƵ ϰϯ More from: Navigating world CC0002 Nanyang… 237 documents Go to course CC0002 Notes P2 Navigating 58 100% (13) world CC0002 LAMS Navigating 23 96% (26) world Wk1 Computational Thinking in Everyday… 3 Navigating 100% (11) world Wk3 Managing Cybersecurity LAMs… 3 Navigating 100% (10) world More from: ntu by Nathanael Sitinjak 8 documents Go to Studylist Engineering Lecture 2019 ALL 201 Mathematics 100% (30) 1 MH1810 Math 1 Guide Tut1-12 42 Mathematics 1 100% (1) PH1011 mindmaps Physics 100% (1) 7 Mathematics 1 Lecture Notes Chapter 5 42 Mathematics 1 None Mathematics 1 Lecture Notes Chapter 4 32 Mathematics 1 None Engineering Mathematics Lecture… 80 Mathematics 1 None

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